Q&A: Approach to frailty population health study with Brent Richards, M.D., M.Sc., Faculty of Medicine at McGill University
We sat down with Brent Richards, M.D., M.Sc., from the Faculty of Medicine at McGill University, to discuss the Canadian population health collaborative study that is aimed at discovering key frailty biomarkers to shed light on why some people become frail, determine the severity of frailty and what can be done to help avoid the condition.
The Canadian Frailty Network, the Canadian Longitudinal Study of Aging (CLSA), the McMaster Institute for Research on Aging (MIRA) and Metabolon, Inc. are part of a collaborative partnership to develop a $4-million research program. Through the endeavor, Metabolon will leverage its proprietary metabolomics platform to analyze blood samples from Canada’s largest and most comprehensive study on aging.
Dr. Richards, what is your interest in this frailty study, and why do you think metabolomics is an integral part of the work?
I am interested in the biological causes of diseases related to frailty. Metabolomics provides an unprecedented opportunity to assess the circulating small molecules that could influence frailty and its associated diseases. This is because new technologies, such as those deployed by Metabolon, allow for the survey of hundreds of different biomarkers. Importantly, such studies do not presuppose that a specific biomarker is important for frailty, but it allows for a more comprehensive search for the metabolites that influence frailty and its associated diseases.
How will the identification of metabolites help to improve the early prediction of frailty, and how will healthcare providers be able to act upon these insights?
There are multiple examples in medicine where biomarkers can predict future disease risk. For example, high cholesterol levels allow for the identification of people at risk of heart attacks. This can be particularly helpful for diseases like frailty where there are interventions that healthcare providers can recommend. Further, such information can help for resource planning and identify people in the population that require enhanced care to deal with the morbidity and mortality associated with frailty. Last, associated biomarkers can sometimes act as therapeutic targets for drug development, which in turn, may help patients by forestalling the diseases associated with frailty.
You’ve worked with genetics a significant part of your career and metabolomics is gaining momentum as a connector that uncovers actionable insights. Can you explain your opinion on how these ‘omics are complementary?
These omics technologies are highly complementary. This is because levels of metabolites are often strongly related to genetic variation. When the genetic variation that influences the level of a metabolite can be reliably identified, this allows for the opportunity to test whether the same genetic variation influences levels of disease. Importantly, this can be done even in studies that have not measured the metabolite but have measured the genetic variation. Since the genetic variants that influence many diseases are now known, this study can be implemented rapidly and help to understand if metabolites are involved in the causal pathway for frailty and disease risk.
When did you first learn about metabolomics, and why has your interest continued to grow in this area?
We have been working in metabolomics for approximately five years by combining this information with genetics. It has been a fruitful area of study and my overlapping the genetic determinants of metabolites and diseases we, and others, have been able to identify compelling new biomarkers for several diseases.
Tell us about your role as co-lead of the CLSA Biomarker/Genetic/Epigenetic Working Group.
I have had the opportunity to co-lead a group of excellent scientists and clinicians from Canada interested in improving the data arising from CLSA. We are excited about opportunities to expand the richness of the data within CLSA and have done so by collaborating with companies like Metabolon. Data resultant from these efforts is available to qualified researchers and it is our hope that the community will embrace this rich data source to provide insights into aging and aging-related disease.
Professor, Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, McGill University
Brent Richards is a professor, William Dawson Scholar and FRQS Clinician Scientist at McGill University and a senior lecturer at King’s College London. Trained in genetics, clinical medicine, endocrinology, epidemiology and biostatistics, Dr. Richards focuses on understanding the genetic determinants of common aging-related endocrine diseases, such as osteoporosis and diabetes. He co-chaired what was world’s largest whole-genome sequencing program for common disease (The UK10K Cohorts Program) and identified a novel and central protein critical to skeletal formation and fracture risk. His work has been recognized through a CIHR Clinician Scientist award, a CIHR Maud Menten award for research excellence in human genetics, and a CIHR/Canadian Society of Endocrinology and Metabolism Young Investigator Award. He is the co-lead of the Canadian Longitudinal Study on Aging Biomarker/Genetic/Epigenetic Working Group.